I want to create an android

I want to create an android like Data on Star Trek. I'm curious what paradigm the AI and robotics community thinks has the best chance of
achieving this? Neural networks? Any comments are appreciated.
Craig
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The AI and robotics community reccomends donating your own brain for the project. You are such an intelligent person, if you transplant your brain into the robot, you will have a superior product.
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snipped-for-privacy@gmail.com wrote:

That's old Star Trek, i.e., "Spock's Brain" episode. I'm talking Star Trek the Next Generation with the android Data.
Craig
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snipped-for-privacy@msn.com wrote:

Actually, if you get a chance, rent 'Saturn 3" with Kirk Douglas and Farrah Fawcett.
Very cool
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good movie
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Just had to inject my two cents in here... If he donated his brain, it would no longer be an android. It would become a cyborg.
An android is a humanoid robot. (entirely artificial, non-biological) A cyborg is a biological/mechanical hybrid, not necessarily humanoid.
Let's keep our terminology straight here!
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snipped-for-privacy@msn.com wrote:

Well who knows? If your level of knowledge in robotics enables you to think that a "Star Trek - Data" type android is possible with current technology, perhaps you should tell us.
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snipped-for-privacy@msn.com wrote:

It is not possible with the current state of human knowledge. If it will ever be possible, it will be far in the future. It is not even known for sure if a digital computer can have a mind like a human, although many members of the AI community believe this as an act of faith. For an excellent presentation of a different view see Roger Penrose's book "The Emperors New Mind".
Mitchell Timin
--
"In theory, there is no difference between theory and practice. In practice,
there is."
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I. Myself wrote:

Why wouldn't it be possible? Admittedly, there isn't much in the way of AI, but programming a mimic of human behavor is not all that difficult. Humans highly overrate the complexity of the behavior of the average human. Seems to me, to make it credible, you'd have to make it act sort of stupid, like human behavior. :-) So, the only problem is the software.
As for neural nets - I expect that is just a passing fad, like bubble memory. Neural nets was an exercise in the study of how neurons work; not a very practical solution to AI, imho.
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well, AI is not able to create anything like that now but when we give birth to AI, i think the first machine compareble to "startreks data" will be created with techniques heavely inspired on the 'process of creation' of ourselves. So my guess it would be something like an EANN (evolutionary artificiall neural network) based on principles from molecular cell biology. eggenberger-hotz is developing EANN's.
if its possible to create 'data' on a symbolic level i think it would be much later.
and dont pay any attention to these spare-time philosophers just remember: they laughed at the wright brother but the also laughed at bozo the clown
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snipped-for-privacy@hotmail.com wrote:

Since you bring up ANNs and Evolution, let me call attention to the URL below, which is devoted to that. There is software there, written in C, that you can download at no charge.
Mitchell Timin
--
"In theory, there is no difference between theory and practice. In practice,
there is."
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Thanks I. Myself,
I look forward to trying out your url.
Craig
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Hello Craig, here is an interesting site that you might enjoy:
http://www.singinst.org /
Cheers,
Dave
snipped-for-privacy@msn.com wrote:

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snipped-for-privacy@msn.com wrote:

Check to see if the positronic brain has been invented yet.
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On 24 Jan 2006 09:35:29 -0800, snipped-for-privacy@msn.com wrote:

The solution will not be as simple as a neural network. Even if it has the same number of neuron as the brain.
Come back in 50 years time and ask again.
--
Steve Wolstenholme Neural Planner Software

EasyNN-plus. The easy way to build neural networks.
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snipped-for-privacy@msn.com wrote:

*********************** C
you question is naive and unsophisticated.
you pose a question that is on the edge or beyond our presence science (at least in the open literature domain)
for clues as others have said study Penrose and wait about 50 years
P
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On 24 Jan 2006 09:35:29 -0800, snipped-for-privacy@msn.com wrote:

The answer is obvious, IMO. Since the only intelligence we know of is biological intelligence and since biological intelligence is made of a number of integregated cell assemblies (neural subnetworks), it follows that future androids will use integrated artificial neural subnetworks as well. However, these subnetworks will bear little ressemblance with current ANNs. For one, biological networks are discrete signal processors, i.e., they process neural spikes. It is an inherently temporal phenomenon.
Why neural networks, you ask? Because it is the only paradigm that can handle the astronomical connectedness of human-level intelligence. Nothing else can come close.
Louis Savain
Why Software Is Bad and What We Can Do to Fix It: http://www.rebelscience.org/Cosas/Reliability.htm
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Traveler wrote:

Before the Wright Brothers, the only flying things we knew of had flapping wings.
Biological systems have limitations that engineered systems do not. The wheel never evolved in a biological system because there is no way to get blood and nerves to a spinning wheel. Birds and insects flap their wings because, lacking propellers or turbines, they use their wings to generate both lift and thrust. But airplanes don't have that constraint, and no airplane was successful till the "flapping" was abandoned.

The human brain uses astronomical connectedness, but that doesn't mean that is the only way to acheive human-level intelligence. That may be the only way to do it within the limitations of biological neurons, but semiconductors have very different limitations. Neurons only switch 10 to 100 times per second. Transistors can switch billions of times per second, so maybe far, far fewer of them are necessary. A biological brain has to be fault tolerant, since thousands of neurons die everyday. Transistors are vastly more reliable than individual neurons. A biological brain has to self-assemble, heal itself, and do a lot of other basic biological activities that a computer does not have to worry about.
Also, biological brains are limited to what evolution can produce. Which means it can creep from one local maxima design to the next, but cannot make dramatic changes. That may work okay for a neural network, but you can't produce a good symbolic algorithm by random evolution "jiggling". Engineers can produce things that would never emerge from evolution.

To the contrary, I don't know of anything that an artificial neural network can do more efficiently than a symbolic algorithm.
It seems to me that the main argument for neural networks is "AI is really hard, so rather than actually trying to understand intelligence, let's just throw a bunch of artifical neurons into a network, and see if it just magically emerges."
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I dont think there is a symbolic solution to the problem. Yes you can add endless pieces of information to your system, yes you can see excactly how its work. BUT when you add line after line to it, you expect the system to "magically" take over and become concious? Because that is what it takes for a symbolic system to become 'mister data'. I think neural networks are the answer, but not the traditional kind we are all familiar of.
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bob the builder wrote:

Any neural network can be simulated using a symbolic algorithm.
Any symbolic algorithm can be simulated by arranging artifical neurons into NAND gates and building a turing machine out of them.
So anything a symbolic algorithm can do, a neural network can also do, and vice versa.
It is simply a question of which approach is more computationally efficient, and which is easier to implement. My opinion is that a symbolic algorithm is always more efficient, and for most problems, is easier to implement as well.

"Conciousness" is ill-defined and subjective. Besides, the goal is "intelligence", not conciousness. I do not expect it to magically emerge. I expect it to incremently improve.
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